---
language:
- en
thumbnail: "images/evaluate/sitting at the edge of a cliff.../sitting at the edge of a cliff_17_3.0.png"
widget:
- text: sitting at the edge of a cliff
output:
url: images/sitting at the edge of a cliff_17_3.0.png
- text: sitting at the edge of a cliff
output:
url: images/sitting at the edge of a cliff_19_3.0.png
- text: sitting at the edge of a cliff
output:
url: images/sitting at the edge of a cliff_20_3.0.png
- text: sitting at the edge of a cliff
output:
url: images/sitting at the edge of a cliff_21_3.0.png
- text: sitting at the edge of a cliff
output:
url: images/sitting at the edge of a cliff_22_3.0.png
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
license: "mit"
inference: false
instance_prompt: "sitting at the edge of a cliff"
base_model: "stabilityai/stable-diffusion-xl-base-1.0"
---
# ntcai.xyz slider - sitting at the edge of a cliff (SDXL LoRA)
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## Download
Weights for this model are available in Safetensors format.
## Trigger words
You can apply this LoRA with trigger words for additional effect:
```
sitting at the edge of a cliff
```
## Use in diffusers
```python
from diffusers import StableDiffusionXLPipeline
from diffusers import EulerAncestralDiscreteScheduler
import torch
pipe = StableDiffusionXLPipeline.from_single_file("https://huggingface.co/martyn/sdxl-turbo-mario-merge-top-rated/blob/main/topRatedTurboxlLCM_v10.safetensors")
pipe.to("cuda")
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
# Load the LoRA
pipe.load_lora_weights('ntc-ai/SDXL-LoRA-slider.sitting-at-the-edge-of-a-cliff', weight_name='sitting at the edge of a cliff.safetensors', adapter_name="sitting at the edge of a cliff")
# Activate the LoRA
pipe.set_adapters(["sitting at the edge of a cliff"], adapter_weights=[2.0])
prompt = "medieval rich kingpin sitting in a tavern, sitting at the edge of a cliff"
negative_prompt = "nsfw"
width = 512
height = 512
num_inference_steps = 10
guidance_scale = 2
image = pipe(prompt, negative_prompt=negative_prompt, width=width, height=height, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps).images[0]
image.save('result.png')
```
## Support the Patreon
If you like this model please consider [joining our Patreon](https://www.patreon.com/NTCAI).
By joining our Patreon, you'll gain access to an ever-growing library of over 870+ unique and diverse LoRAs, covering a wide range of styles and genres. You'll also receive early access to new models and updates, exclusive behind-the-scenes content, and the powerful LoRA slider creator, allowing you to craft your own custom LoRAs and experiment with endless possibilities.
Your support on Patreon will allow us to continue developing and refining new models.
## Other resources
- [CivitAI](https://civitai.com/user/ntc) - Follow ntc on Civit for even more LoRAs
- [ntcai.xyz](https://ntcai.xyz) - See ntcai.xyz to find more articles and LoRAs